Software Engineer - ML

Lowe's; Town of Florida (NY); On-site; USD 120,000 - 150,000; Full time

Job summary

Lowe's seeks a skilled AI/ML Engineer to help build forecasting models, data pipelines, and production-ready ML systems. You will collaborate with data scientists, product, and business teams to translate requirements into scalable, reliable AI/ML solutions.

Join Lowe's forecasting platform team to design, deploy, and maintain end-to-end ML pipelines, ensure data quality, and optimize performance in cloud and on-prem environments. Strong emphasis on SDLC, DevOps, and governance.

Qualifications

• Bachelor's degree in computer science, computer information systems, or related field.
• 2 years of software development experience.
• 2 years of SDLC/iterative agile development experience.
• 2 years experience with frontend, middleware, database, or DevOps.

Responsibilities

• Build and maintain scalable data ingestion, transformation, feature engineering, and post-processing pipelines for model training, inference, analytics, and reporting.
• Collaborate with Data Scientists, Product, and Business teams to translate requirements into scalable AI/ML data pipelines.
• Design, develop, deploy, and maintain end-to-end ML systems including packaging, versioning, deployment, and serving using MLflow, Kubeflow, Vertex AI or similar tools.
• Build and optimize batch and real-time inference pipelines for performance, scalability, and cost efficiency across cloud and on-prem environments.
• Implement CI/CD pipelines and workflow orchestration for AI/ML models and data pipelines following DevOps/MLOps best practices.

Skills

Apache Airflow

Cloud Composer

GCP

BigQuery

Trino/Presto

Great Expectations

Retail forecasting

Time series forecasting

Data quality

ML deployment

Education

Bachelor's degree in computer science or related field

Tools

MLflow

Kubeflow

Vertex AI

Job description

Innovate in Charlotte

Thank you for dedicating your time and talent to Lowe's. We want to give you more opportunities to learn and grow, so if you find a position you're interested in below, we encourage you to apply!

Your Impact

The primary goal is to generate AI/ML forecasts that help the business plan for future demand, optimize resources, reduce risk, and make data-driven decisions. Lowe's forecasting platform team is responsible for predicting future trends, outcomes, or events based on current and historical data.

Work with a Winning Team

As part of a Fortune 50 company and retail leader, your work can change an entire industry. Our CEO is a forward‑thinker when it comes to tech, and with one of Forbes Top 50 CIOs leading the charge, you can come to work knowing you'll have access to the data, tools, and support that few other companies can offer. We also know what it takes to create an inclusive culture that supports you.

Our teams are structured around the engineer, giving you the support you need to do your best work. Since we've been in business for over 100 years, we've built an excellent track record of growth and success. There's peace of mind knowing you have the stability and resources you need to focus on solving tough challenges. And as you solve these challenges, know you'll be surrounded by supportive associates with curious minds who listen to you, respect you, and recognize your hard work.

What You Will Do

• Build and maintain scalable data ingestion, transformation, feature engineering, and post‑processing pipelines to support model training, inference, analytics, and reporting.
• Collaborate with Data Scientists, Product, and Business teams to translate business requirements into scalable AI/ML solutions and production‑ready data pipelines.
• Design, develop, deploy, and maintain end‑to‑end ML systems, including model packaging, registration, versioning, deployment, and serving using platforms such as MLflow, Vertex AI, Kubeflow, or similar MLOps tools.
• Build and optimize batch and real‑time inference pipelines for performance, scalability, reliability, and cost efficiency across cloud and on‑premises environments.
• Implement and maintain CI/CD pipelines and workflow orchestration for AI/ML models and data pipelines using DevOps and MLOps best practices.
• Design and implement monitoring frameworks to track model performance, data quality, data drift, model drift, and production system health.
• Build reusable libraries, utilities, and platform components that improve engineering productivity and standardize ML development across teams.
• Develop production‑quality software components following software engineering best practices, ensuring solutions are scalable, testable, maintainable, and efficient.
• Perform root cause analysis, troubleshoot production issues, and participate in code reviews to improve code quality, reliability, and operational excellence.
• Ensure AI/ML solutions comply with security, governance, privacy, and organizational standards throughout the development lifecycle.
• Champion engineering best practices to continuously improve the reliability, scalability, maintainability, and operational efficiency of AI/ML platforms and pipelines.

Skill Set requirements

Apache Airflow, Cloud Composer, GCP cloud experience, Big Query, Trino/Presto. Experience working on Data Quality/Integrity theme, Tools like Great Expectations. Domain experience on retail forecasting or any other business forecast predictions/time series forecasting.

Minimum Qualifications

• Bachelor's degree in computer science, computer information systems, or related field or equivalent years of experience in lieu of education requirement, if applicable
• 2 years of experience in software development or a related field
• 2 years of experience working on project(s) involving the implementation of solutions applying development life cycles (SDLC) through iterative agile development
• 2 years experience working with any of the following: frontend technologies (user interface/user experience), middleware (microservices and application programming interfaces), database technologies, or DevOps

Preferred Skills/Education

• Minimum 2 years of experience developing production software and AI/ML applications with large datasets.
• 2 years of experience writing technical documentation in a software environment and developing and implementing business systems within an organization
• 1+ year of experience delivering solutions using Agile methodologies and Software Development Life Cycle (SDLC)
• Must be well‑versed with ML system deployment/release process with live inference, batch inference, and model versioning.
• Experience with Data Engineering and building data/ML pipelines.
• Hands‑on experience building robust, reliable, and scalable AI/ML pipelines.
• Experience with MLOps tools such as MLflow, Kubeflow, or Vertex AI.
• Foundational understanding of ML models.
• Strong understanding of cloud platforms (GCP, AWS, or Azure)